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Drought forecasting is a critical aspect of water resource management, where droughts have substantial economic and environmental impacts. This study employs a Monte Carlo–based approach, complemented by statistical distribution fitting and trend analysis, to forecast future streamflows on long-narrow type drainage basins. Therefore, the Kızılırmak River Basin in Turkey, which is a long and narrow type, has been selected to test the suggested method. Historical data are used to determine the best-fitting distributions, ensuring reliability in the selection of future streamflow scenarios also using trend analysis. The study reveals valuable insights into potential drought occurrences over the next 25 years, aiding decision makers in implementing water management strategies. Based on the analysis results, it is expected that the drought frequency is increased up to 64.7%. Drought severity is classified into different categories, offering an understanding of drought characteristics. The findings contribute to effective water resource planning by aiming the assessment of future hydrological droughts. [ABSTRACT FROM AUTHOR]

The probability distribution function (PDF)-based unit hydrographs (UHs) are gaining momentum in an application for more accurate rainfallrunoff transformation. Employing seven statistical performance indices, R2, NSE, MSE, RMSE, MAE, MAPE, and SE in generalized reduced gradient nonlinear programming (GRG-NLP) optimization, 18 known and 12 adaptable PDF-based UHs were assessed against UHs derived from 18 storms in 7 basins across the United States, Turkey, and India. To this end, 27 Maple codes were proposed for UH-application requiring only peak discharge (qp), time to peak (tp), and time base (tb) for derivation. The introduced PDFs, such as Dagum, Generalized Gamma, Log-Logistic, Gumbel Type-I, and Shifted Gompertz, replicated the observed data-derived UHs more closely than did the known PDFs, like Inverse Gaussian, two-parameter gamma distribution (2-PGD), Log-Normal, Inverse-Gamma, and Nagakami. Among the three-parameter (6 nos.), two-parameter (21 nos.), and single-parameter (3 nos.) PDFs, the Dagum, Log-Logistic, and Poisson consistently outperformed their respective counterparts in replication. [ABSTRACT FROM AUTHOR]

In current engineering practice, the torsional effects of ground motions are only considered implicitly through "accidental eccentricity coefficients". In seismic design codes, these coefficients account for not only the unintended (or uncertain) asymmetric distributions of structural mass and stiffness in the plan but also the torsional components of ground motions. The torsional effects may develop due to wave passage effects or the incoherency of translational ground motions along the foundation systems. While it is possible to obtain torsional components of ground motions directly from seismic records with modern instruments, such sensors are uncommon. Therefore, several numerical procedures have been proposed in the literature for estimating torsional components of ground motions from translational measurements. In this study, the Single Station Procedure (SSP)—based on the deconstruction of translational ground motions into body waves and the subsequent reconstruction of rotational ground motions—is employed to obtain torsional ground motions for seven different seismic events in Turkey. Additionally, the corresponding accidental eccentricity coefficients that can cause the same response modification with torsional ground motions are determined. First, a conventional procedure is utilized to obtain the corresponding accidental eccentricity coefficients. Various drawbacks of the conventional procedure, such as negative eccentricity coefficients, are addressed. Then, a relatively obscure definition of accidental eccentricity is revived to propose a novel procedure for determining accidental eccentricity coefficients. It is observed that the proposed procedure yields higher values for the accidental eccentricity coefficients than the conventional procedure. It also observed that the torsional spectrum provided in Eurocode 8 provisions requires higher eccentricity values than those implied by the recorded ground motions from Turkey. [ABSTRACT FROM AUTHOR]

The effects of global warming and climate change appear as increasing or decreasing trends in hydrometeorological records in different locations. Identifying trends in long-term (more than 30 year) data is possible through a variety of methodologies as well as classical Mann–Kendall (MK), Regression (R), Spearman's Rho (SR) methods in addition to the innovative trend analysis (ITA) approaches. The most used method in the literature is the MK trend determination test, but it has limited assumptions, and the trend slope is calculated according to Sen's median procedure. However, Sen's approach is an empirical methodology that considers a single median slope from all possible consecutive lag slopes. This paper provides the theoretical probability distribution function (PDF) that matches Sen's slopes, and an innovative probabilistic trend slope methodology is proposed with a set of slope risk levels, rather than statistical slope calculation. The application of the proposed methodology is presented for long-term Danube River annual discharge data in Romania and precipitation records at Antalya resort center in the south along the Mediterranean coast of Turkey. A set of trend lines, objectively different risk levels, are obtained. It has been determined that there are decreasing and increasing monotonic trends in each historical time series record. Therefore, for extreme events, it is possible to consider a particular risk level trend characteristic, i.e., floods and droughts, rather than the classical mean or median level trend definition. [ABSTRACT FROM AUTHOR]

In the open literature, there are numerous studies on the normal and extreme (flood and drought) behavior of wet and dry periods based on the understanding of the standard precipitation index (SPI), which provides a series of categorizations by considering the standard normal (Gaussian) probability distribution function (PDF). The numerical meaning of each categorization assessment is quite lacking in terms of future predictions of wet and dry period duration based on historical records. This paper presents a new approach for calculating possible formations of future wet and dry period durations based on historical records through an effective fractal geometric forecasting approach. The essence of the proposed methodology is based on the number of dry periods (steps) of non-overlapping monthly duration along consecutive broken line paths in the SPI classification for wet and dry period durations. It has been observed that the plot of periods on double logarithmic paper falls along a straight line against the number of such periods, implying a power function, which is the essence of fractal geometry. Extending the empirically derived straight line provides the number of periods that may occur in the future over a range of SPI levels. This methodology is referred to as SPI fractal (SPIF), and the classic SPI classification is converted into SPIF wet and dry polygons, which provide additional information about the drought period number within a valid polygonal area, compared to the classic SPI results. The wet and dry period features of any hydro-meteorology time series are constrained in SPIF polygons. The application of the methodology was carried out on monthly rainfall records on the European side of the Istanbul Florya meteorological station in Turkey. [ABSTRACT FROM AUTHOR]

Besides being a devastating and long-lasting disaster, a drought is an event that affects a large area. It is essential to determine the duration, severity, and magnitude of the drought in the determination and evaluation of the measures. The disruption of rain-based activities in the Black Sea coasts, the wettest areas in Turkey, will cause agricultural production to decrease and the region's people to be negatively affected economically. Analysing the meteorological drought due to precipitation in the region will help to reduce the effects of such adverse events. In the present study, three homogeneous regions were identified using the fuzzy C-means clustering method (FCM), and drought characteristics (e.g. severity (S), duration (D), and magnitude (m)) were calculated based on the standardised precipitation index (SPI). The trivariate risk analysis of meteorological drought was performed using copulas, goodness-of-fit test statistics, and graphical methods. The L-moment ratio diagram for drought duration in all homogeneous regions showed that among the five distributions, the best distribution function was determined for the severity and duration of drought as PE3 regions and the magnitude of drought as GPA. The copula goodness-of-fit statistics showed that the Joe copula in all homogeneous regions is the best. Based on the results, the west coast of the Black Sea is under high conditional drought risk, and inland and eastern coastal are under low conditional drought risk in the S≤20 and D≤20 episodes, for m=0.2. Nevertheless, with the increase of m value, the area at risk of drought is growing; moreover, the entire region considered for m=0.75 and 1 is very high risk. The conditional risk analysis can be helpful for the decision-makers to maintain agricultural activities and prevent this region, which plays a vital role in the country's exports. [ABSTRACT FROM AUTHOR]

In recent years, wind energy has become remarkably popular among renewable energy sources due to its low installation costs and easy maintenance. Having high energy potential is of great importance in the selection of regions where wind energy investments will be made. In this study, the wind power potential in Çanakkale Province, located in the northwest of Türkiye, is examined, and the wind speed is estimated using hourly and daily data over a one-year period. The data, including 12 different meteorological parameters, were taken from the Turkish State Meteorological Service. The two-parameter Weibull and Rayleigh distributions, which are the most widely preferred models in wind energy studies, are employed to estimate the wind power potential using hourly wind speed data. The graphical method is implemented to calculate the shape (k) and scale (c) parameters of the Weibull distribution function. Daily average wind speed estimation is performed with artificial neural network–genetic algorithm (ANN-GA) and ANN–particle swarm optimization (ANN-PSO) hybrid approaches. The proposed hybrid ANN-GA and ANN-PSO algorithms provide correlation coefficient values of 0.94839 and 0.94042, respectively, indicating that the predicted and measured wind speed values are notably close. Statistical error indices reveal that the ANN-GA model outperforms the ANN-PSO model. [ABSTRACT FROM AUTHOR]

The purpose of seismic microzonation is to estimate earthquake characteristics on the ground surface based on a probabilistic approach to mitigate earthquake damage in the foreseeable future for the new buildings, as well as for the existing building stock. The probabilistic analysis and related results are very important from an engineering perspective since the nature of the problem can only be dealt with in a probabilistic manner. The uncertainties associated with these analyses may be large due to the uncertainties in source characteristics, soil profile, soil properties, and building inventory. At this stage, the probability distribution of the related earthquake parameters on the ground surface may be determined based on hazard-compatible input acceleration-time histories, site profiles, and dynamic soil properties. One option, the variability in earthquake source and path effects may be considered using a large number of acceleration records compatible with the site-dependent earthquake hazard. Likewise, large numbers of soil profiles may be used to account for the site-condition variability. The seismic microzonation methodology is proposed based on the probabilistic assessment of these factors involved in site response analysis. The second important issue in seismic microzonation procedure is the selection of microzonation parameters. The purpose being mitigation of structural damage, it is possible to adopt earthquake parameters like cumulative average velocity (CAV) or Housner intensity (HI) that was observed to have better correlation with building damage after earthquakes. A seismic microzonation procedure will be developed with respect to ground shaking intensity considering probabilistic values of the cumulative average velocity (CAV) or Housner intensity (HI). [ABSTRACT FROM AUTHOR]

Wave energy is recognized as a significant renewable energy source with a high energy density and very low environmental impact. Today, in parallel with the developments in wave energy technologies, the interest of designers, investors and researchers increases rapidly. Knowledge of wave characteristics is needed to construct and plan wave energy generation systems in any basin. In this respect, determining the probability distribution function of the mean wave period and significant wave height is of vital importance for optimum and reliable planning, and installation of wave energy generation systems. The aim of this study is to examine wave power potential in the North Aegean Sea using the Weibull and Rayleigh probability density models in order to achieve the intended results, a data set such as hourly significant wave height, mean wave period, and wave direction covering one year were used. In agreement with the calculation results, the annual average wave power potential, mean wave period, and significant wave height of this buoy measurement point in the North Aegean Sea were obtained as 1.0145 kW/m, 4.1702s, and 0.5573 m, respectively. This information is essential for power plant operators and policy makers to define the development opportunities, benefits, and costs of developing Turkey's wave energy converter industry. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to examine whether there is a relationship between impulse purchasing behaviour and lifestyle. It is necessary to understand the lifestyle types of consumers, who are heavily influenced by the sales and communication activities implemented by businesses and are inclined to engage in impulse purchasing behaviour. Impulse purchasing is encouraged in consideration of the tough competition between businesses. The population of the research is Duzce, which is one of the provinces that best represents Turkey due to its cosmopolitan structure and developed industry. More than 500 individuals were reached by employing the purposeful sampling method, and brief information about the research was given to them. Finally, 394 of them who had full knowledge of the subject were selected for the study. Frequency distribution, factor, correlation, regression, t test and ANOVA tests were applied to the obtained data. According to the frequency distribution results, the participants generally had prepared a list of needs (63%), purchased products that were not needed (80%), and defined themselves mostly as organizers, citizens and innovators. Based on the results of factor analysis, seven factors related to lifestyle emerged. These are the experiencers, strives, makers, believers, innovators, achievers, and survivors. A single factor has emerged in the impulse purchasing behaviour. According to the results of the correlation analysis, significant and positive relationships emerged between all subdimensions of lifestyle and impulse purchasing behaviour. The highest correlation was found between survivors and insurgent to impulse purchasing behaviour. Regarding the results of the regression analysis, it was concluded that the survivors, experiencers, and insurgent individuals under the lifestyle subdimensions had a significant and positive effect on impulse purchasing behaviour. According to the difference analysis, it has been revealed that lifestyle-oriented females have a more positive perception than males, singles than married, those who prepare a list of needs than those who do not, those with high incomes than those with low incomes, and middle-age groups than other groups. It has also been revealed that private sector employees had a more positive perception than those who were self-employed, unemployed, students and other professional groups. In the dimension of impulse purchasing behaviour, it was concluded that secondary school graduates had a more positive perception than the others and those who prepare need lists compared to those who do not prepare need lists. When the results are evaluated, it can be concluded that the lifestyle types that have the most impact on impulse purchasing behaviour are those who are strives, survivors, and experiencers. [ABSTRACT FROM AUTHOR]

The author of this paper has recently shown that daily-mean self-potential (SP) time series recorded at Urla station, Turkey, exhibit a unit-root nonstationary behavior with weakly correlated stationary differences driven by stable noise of tail index around 1.12–1.15. This work mainly aims to assess whether the Exponentiated-Exponential Cauchy (EEC) family distributions could be utilized as an alternative to the stable distributions. The EEC family distributions have many advantages as they have closed-form representations. Those goodness-of-fit statistics, relative strengths and predictive abilities of the three EEC family distributions with two- (Cauchy), three- (EEC-3) and four (EEC-4) parameters were compared with that of the stable one. The Akaike Information Criterion (AIC)-based relative strength for the EEC-3 candidate indicated that it is approximately 1.85 times more likely to be the best approximating model than the stable one. Additionally, those considerably smaller relative mean absolute errors (RMAE) for the EEC-3 model indicated that the asymptotic tail properties of the empirical distribution could be better represented in comparison with the stable model. The results of this work revealed, on the example of Urla, that an EEC-3 distribution would plausibly the stable one. We hope the findings of this paper would provide many advantages and facilitate the numerical computations in solving problems arising from the use of stable laws. [ABSTRACT FROM AUTHOR]

Two strong earthquakes occurred in Turkey on 6 February 2023, at 01:17:34 (nighttime, Mw = 7.8) and at 10:24:50 UT (daytime, Mw = 7.5). The seismo-ionospheric impact is an important part of the near-Earth environment state. This paper provides the first results on the ionospheric effects associated with the aforementioned earthquakes. We used data from global navigation satellite system (GNSS) receivers and ionosondes. We found that both earthquakes generated circle disturbance in the ionosphere, detected by GNSS data. The amplitude of the ionospheric response caused by daytime M7.5 earthquake exceeded by five times that caused by nighttime M7.8 earthquake: 0.5 TECU/min and 0.1 TECU/min, respectively, according to the ROTI data. The velocities of the earthquake-related ionospheric waves were ~2000 m/s, as measured by ROTI, for the M7.5 earthquake. TEC variations with 2–10 min periods showed velocities from 1500 to 900 m/s as disturbances evolved. Ionospheric disturbances occurred around epicenters and propagated to the south by means of 2–10 min TEC variations. ROTI data showed a more symmetric distribution with irregularities observed both to the South and to the North from 10:24:50 UT epicenter. The ionospheric effects were recorded over 750 km from the epicenters. Ionosonde located 420/490 km from the epicenters did not catch ionospheric effects. The results show significant asymmetry in the propagation of coseismic ionospheric disturbances. We observed coseismic ionospheric disturbances associated with Rayleigh mode and acoustic modes, but we did not observe disturbances associated with acoustic gravity mode. [ABSTRACT FROM AUTHOR]

The poultry sector provides people and countries with many benefits in the social, economic and health domains. However, the poultry sector faces a number of important problems. One of these problems is information pollution. The rapid advances in information and communication technologies, in particular, made information pollution one of the most important problems of our contemporary age. Information pollution can have significant negative effects on companies and sectors, as well as threaten the reputation of the brand, the products and services offered by the businesses. The poultry industry is among the most affected by information pollution and Turkey represents an ideal case for studying the effects of information pollution on the poultry industry. The poultry sector has achieved significant growth in Turkey in recent years, but the problem of information pollution is an important factor that limits this growth. There are ongoing efforts by various organizations and agencies in Turkey to solve the problem. This study aims to examine the effects of information pollution on poultry producing companies in Turkey and identify the activities undertaken by producers to fight information pollution. Data were collected from companies that are members of BESD-BİR (Turkish Poultry Meat Producers and Breeders Association), which brings together the largest chicken producing companies in Turkey and account for 91% of all poultry production in Turkey. Basic statistical techniques and procedures such as frequency distributions, percentages, and arithmetic means were used to conduct descriptive statistical analysis. Likert-type questions were also included in the study for various purposes. Descriptive analysis method was used to analyze the suggestions made by the poultry producers to reduce information pollution in the sector. The results show that information pollution problem is an important problem for poultry producing companies in Turkey. Since a significant part of the companies are affected by the problem of information pollution, they have various activities aimed at solving this problem and informing consumers. The problem has slight to moderate effects on the sales, production decisions, marketing decisions, and investment decisions. It has been found that sales and production decisions are affected to a slightly larger extent compared to marketing and investment decisions. Poultry producing companies consider it important to carry out successful information campaigns and increase cooperation in the sector in order to solve information pollution problems. [ABSTRACT FROM AUTHOR]

While earthquakes can have a devastating impact on the economic growth and social welfare of earthquake prone regions, probabilistic seismic risk assessment can be employed to assess and mitigate such risks from future destructive events. In a previous study (Sianko et al. in Bull Earthq Eng 18:2523–2555, 2020), a probabilistic seismic hazard analysis (PSHA) tool based on the Monte-Carlo approach, was developed to predict the seismic hazard for high seismicity areas. In this study, a seismic risk assessment framework is developed incorporating the previously developed PSHA tool, with vulnerability functions based on various damage criteria, exposures and casualty models. Epistemic uncertainty is addressed using logic trees and distribution functions. The developed seismic risk assessment framework can estimate human and economic losses for particular return periods using an event-based stochastic procedure. The framework is applied to a case study area, the city of Adapazari in Turkey. Seismic risk assessment is carried out for different return periods to identify the most vulnerable areas of the city. The verification of the developed seismic risk framework is performed by comparing the predicted seismic losses to those observed during the 1999 Kocaeli earthquake that severely affected the city of Adapazari. The results of the study indicate that while overall predictions for extensive and complete damage states demonstrate strong correlation with the observed data, accurate risk predictions at the district level are not achievable without microzonation studies. [ABSTRACT FROM AUTHOR]

Censoring, extreme values, and non-normal distribution are common features in microdata. These data features can compromise the statistical distributions of the estimators when an appropriate model is not used. We use an inverse hyperbolic sine (IHS) transformation in the double-hurdle (DH) model to accommodate extreme values and skewness in censored accommodation spending among Turkish households. The full-parameterized model nests many restricted specifications which do not accommodate dependence, heteroscedasticity, and non-normality in the error terms. Statistical test results support the use of the fully parameterized dependent IHS-DH specification. The statistically significant correlation between the binary and level decisions of accommodation precludes the use of a model with a two-step structure. Some of the findings in our study have a determining or driving force in expressing causality relationship in monthly accommodation probability and level decisions. The study made also prudent policy recommendations about what the results might mean to policymakers and stakeholders. [ABSTRACT FROM AUTHOR]

Owning to climate changes and other anthropogenic interventions, the frequency and return levels of extreme flows cannot be treated as stationary. This study quantifies the changes in return levels by fitting the stationary and nonstationary frequency distribution models for annual and seasonal high and low flows of upper Euphrates basin during historical and two projection periods. The projected flows of three selected sub-basins in the upper Euphrates were obtained using HBV-light hydrological model forced by projected daily precipitation and temperature driven from and the most representative regional climate model (RCM) for the study area within the CORDEX-Euro domain. During the historical period, analyses suggest that half of the stations exhibited an increase in return levels (up to 13.5% with GEV), while the remaining four sub-basins experience a decrease in the return levels (up to 27% with GEV). With few exceptions, most of the sub-basins experience an increase (up to 80% with GEV) in return levels of yearly low flows. With few exceptions, the return level of low flows for all seasons generally increases; however, directional variability for high flows is observed. The changes in return levels of yearly projected flows are consistent with historical results in indicating the direction of impact for both near future and far future periods. A decrease in return levels (up to 35% and 22%) in yearly high flows and an increase (up to 100% and 40%) during the near future and far future, respectively. It is projected that the floods of a given return level in the selected sub-basins are becoming milder across all three periods. However, some directional inconsistencies are noted in nonstationarity impact at seasonal scale through projection periods. On yearly basis, the decreasing high flow along with increasing low flow quantiles suggests that the range of extreme occurrences is shrinking. The nonstationarities in high flows as well as low flows should be incorporated in design and development of water resources schemes in the study area. [ABSTRACT FROM AUTHOR]

The doubt in the calculation algorithm of the standardized precipitation index (SPI), which is widely preferred in the evaluation and monitoring of drought, still remains up-to-date because its calculation process is performed in the form of standardization or normalization with a default probability distribution. Therefore, the success of this index is directly affected by the choice of the probability distribution model. This study is based on the effect of three different parameter estimation methods on the calculation process, as well as the comparison of the SPI results calculated based on the default Gamma distribution and the distribution with the best ability to represent the 3-and 12-month consecutive summed rainfall data among the 15 candidate distributions namely Gamma (GAM), Generalized Extreme Value (GEV), Pearson Type III (P III), Log Pearson Type III (LP III), two-parameter Lognormal (LN2), three-parameter Lognormal (LN3), Generalized Logistic (GLOG), Extreme Value Type I (EVI), Generalized Pareto (GPAR), Weilbul (W), Normal (N), Exponential (EXP), Logistic (LOG), four-parameter Wakeby (WK4), and five-parameter Wakeby (WK5) distributions. Approximately 68.4% and 18.4% of the 3-month data considered had the best fit to the Weibull and Pearson III distribution, while approximately 24% and 18% of the 12-month data had the best fit to the Weibull and Logistic distribution. On the other hand, it was found that the default Gamma distribution calculated the extreme drought categories significantly more than the best-fit distribution model. In terms of parameter estimation methods, L-moments for 3-month series and maximum likelihood approaches for 12-month series were most dominant. [ABSTRACT FROM AUTHOR]

Drought, one of the main factors threatening social life today, is examined and analyzed by its types such as meteorological, agricultural, and hydrological droughts. Thus, decision-makers need advanced methods in monitoring and assessing the drought, which is important for future plans. Multivariate drought indices were developed to allow determining the actual and real level of drought by reducing the deficiencies of current methods. In a region having three different characteristics (BSk: semiarid cold, Csa: dry summer–hot summer, and H: unclassified highland), MSDI was modeled by utilizing the data from Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Surface Runoff Index (SRI). For the period between 2003 and 2021, the precipitation, evapotranspiration, and surface runoff data were obtained from SPEI Global Drought Monitor and ERA5 databases. Gaussian function was used in establishing the copula-based joint distribution functions according to AIC, BIC, and max-likelihood assessment criteria. The R packages offering a wide range of use for drought modeling and assessment based on the multivariate drought indices were used. The calculations performed for 4 different time scales as MSDI 1-3-6-12 (soil moisture, surface hydrology, and agricultural and hydrological perspectives) showed acceptable performance in multivariate estimation of the drought. It was determined that, for all four time scales (1, 3, 6, and 12 months), MSDI values obtained from modeling were more similar to SPEI values in comparison with SRI values. Considering all the data, it was determined that the years 2007 and 2016 were found to be the driest years for the basin on the 6-month scale, whereas the years 2016 and 2021 were the driest years on the 12-month scale. [ABSTRACT FROM AUTHOR]

In recent times, copula families have been mostly employed in bivariate drought duration and severity. Archimedean copulas are mainly used conveniently among various potential families for hydrologic design and water resource management. In this study, drought events are defined by standard precipitation index (SPI3 time series) series for 24-gauge stations in Ceyhan Basin Turkey considering different elevation levels (high, average, and low). Both duration and severity are tested for their dependence with Mann–Kendall and Spearman Rho trend test at a 0.05 significant level. While Gamma and Weibull perform better than the other distributions at average elevation, Log-normal and Weibull distributions are found to fit the DD and DS series better for most stations located in low and high elevations, respectively. The best fit copula is found to construct a joint distribution function. The influence of upper tail dependencies is tested to select the most appropriate copula function. Gumbel and BB1 copulas are often regarded as the best copulas for the DD and DS series, respectively. After acquiring the best fit copula, the joint return periods are modeled for each station. Finally, considering drought risk categories (mild, moderate, severe, and extreme drought), spatial distributions of drought risk-return period are constructed. High risks are observed in the middle part of the basin based on TDS and T′DS under mild drought categories. Apart from using univariate frequency analysis, bivariate frequency analysis is performed to model the joint return period based on copula theory which is great of importance for hydrology design and water resource management. [ABSTRACT FROM AUTHOR]

The determination of wind speed characteristics is extremely important for estimating the wind power output. In this context, Weibull distribution is one of the most commonly used statistical distributions for modeling wind speed. However, despite its widespread usage, it may not be accurate for modeling all wind regimes. For this reason, alternative distributions are utilized for modeling wind speed data. In this study, we use Rayleigh, Inverse Weibull (IW), Burr Type III, Extreme Value (EV), Gamma, Inverse Gamma (IG), Marshall–Olkin extended Lindley (MOEL), generalized Extreme Value (GEV) and exponentiated Weibull (EW) distributions as alternatives to Weibull. Our aim is to determine the distribution which provides the best fit for different wind regimes encountered in nature. In the application part, data sets are taken from stations located on Turkey's Aegean coast and the fitting performances of the above-mentioned distributions are compared. In order to determine the appropriate wind speed distributions. Different model selection criteria are utilized. [ABSTRACT FROM AUTHOR]

Retail companies monitor inventory stock levels regularly and manage them based on forecasted sales to sustain their market position. Inventory accuracy, defined as the difference between the warehouse stock records and the actual inventory, is critical for preventing stockouts and shortages. The root causes of inventory inaccuracy are the employee or customer theft, product damage or spoilage, and wrong shipments. In this paper, we aim at detecting inaccurate stocks of one of Turkey's largest supermarket chain using the variational autoencoder (VAE), which is an unsupervised learning method. Based on the findings, we showed that VAE is able to model the underlying probability distribution of data, regenerate the pattern from time series data, and detect anomalies. Hence, it reduces time and effort to manually label the inaccuracy in data. Since the distribution of inventory data depends on selected product/product categories, we had to use a parametric approach to handle potential differences. For individual products, we built univariate time series, whereas for product categories we built multivariate time series. The experimental results show that the proposed approaches can detect anomalies both in the low and high inventory quantities. [ABSTRACT FROM AUTHOR]

In this study, we present the long‐term daily and subdaily station data of annual extreme rainfall (1970–2015) and the trend analyses in rainfall regimes in Turkey. Trends in 5, 10, 15, and 30 min, 1, 2, 6, 12, and 24 hr of extreme rainfall in seven different rainfall regimes are estimated through nonparametric tests. The trends in return levels (2, 20, and 100 years) are defined by an appropriate three‐parameter generalized extreme value distribution and are evaluated in the climatological context of rainfall regimes. Overall, from 5‐min to 2‐hr durations, magnitudes of trends in extreme rainfall constantly increase in all rainfall regimes, which may be attributed to the intensified contribution of convective rainfall as a response to warming. Trend analysis of return levels reveals that, compared with 2‐year return levels, low‐probability high‐impact extreme rainfall events generally have the lowest estimated median trends until 30‐min to 2‐hr range. A shift in the magnitudes of trends occurs generally at 30‐min and 1‐hr durations; trends of rare intense events increase at the expense of less intense extreme rainfall. Thus, the intensification of 1–2‐hr extreme rainfall events can arise from both the increasing trends of more common events in shorter rainfall durations and from the increase in the trends of low‐probability high‐impact extreme rainfall events at this range. Moreover, explicitly in continental rainfall regimes, increases in the magnitudes of the trends in 30‐min to 2‐hr duration range are accompanied by various declines in 6–24‐hr duration range. Although coastal regimes generally have increasing trend values from 5‐min to 24‐hr durations, in northern and southern clusters, changes occur in the variability of extreme rainfall and the trend values of rarer (20‐ and 100‐year return periods) extreme rainfall exhibit increases in 6–12‐hr range. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Language Academy is the property of Rota Kariyer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Energy consumption in buildings accounts for a notable part of the primary energy consumption all over the world. The building industry also has a great potential to decrease the environmental impact by reducing greenhouse gas emissions. The national strategies of many developing countries are shaped by energy conservation issues. Improving energy efficiency and productivity is stated as one of the main elements of the Turkish national energy strategy. An efficient way to decrease energy consumption in buildings is to implement insulation on the building envelope. Identifying the optimum insulation thickness to be applied on the exterior walls is of prime importance. This study adapts a stochastic approach to determine optimum insulation thickness for 81 cities in Turkey. The stochastic approach, unlike the commonly used deterministic approach, incorporates the probabilistic nature of the process and presents the optimum insulation thickness as a probability distribution graph rather than a single value. For this purpose, a number of insulation thicknesses (1-20 cm) were regarded as the alternatives and the optimum alternative was determined based on life cycle costing analysis involving the cost of insulation application and annual energy savings. The average monthly temperature of each city and financial parameters such as the inflation and discount rates were considered as the stochastic elements. The results of the life cycle costing analysis were used to (i) identify the optimum thicknesses in each city as a probability distribution graph and (ii) generate an optimum insulation thickness map for Turkey. [ABSTRACT FROM AUTHOR]

Copyright of Conservative Thought / Muhafazakar Düşünce is the property of Muhafazakar Dusunce Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the current study, the chemical fractions of Pb and Cd and total concentrations of these metals in topsoil samples which were collected between 2016 and 2017 in the center of Mugla, which is a small agricultural city in the Aegean Region of Turkey, were determined. Contamination, environmental, and potential human health risks indices were calculated in topsoil samples for Cd and Pb. In order to determine the exchangeable, reducible, oxidizable, and residual fractions of Cd and Pb in topsoil samples, the modified BCR chemical sequential extraction procedure was used. According to contamination and environmental risk indices, only Cd could pose a serious risk for the center, but Pb had no risk. But according to potential human health risk indices in the topsoil samples, no harm to human health was determined for both metals. The results of the study showed that total concentrations of Cd in the topsoil samples in all the locations of the center of Mugla had a uniform distribution. However, the chemical fractions of the metals did not show a uniform distribution and very different fraction values were obtained for Cd and Pb in each location of the city. In addition, it was determined that the concentrations of Cd in the topsoil samples exceeded the maximum permissible limits for some international soil quality guidelines but the concentration of Pb in topsoil samples did not exceed these limit values. [ABSTRACT FROM AUTHOR]

Copyright of Bartin University Journal of Faculty of Education is the property of Bartin University Journal of Faculty of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Eskişehir Basin, which is a graben depression in Central Anatolia, has been subjected to ground shaking that has led to destructive earthquakes in the past. It is expected that most of the 108,807 structures built on the alluvial sediment in the study area will be subject to the effects of spectral soil amplification. Fast and economical assessment methods can be used to determine the sediment depth. In this study, an approach to compute the depth of the alluvial soil in urban residential areas using microtremor measurements is presented through the example of the Eskişehir graben. Microtremor measurements were carried out at 741 points at variable intervals of 200 m and 1000 m depending on the density of the residential area. The results showed that the dominant frequencies were from 0.2 to 15 Hz. The alluvial sediment in the Eskişehir graben was associated with the third peaks in the dominant frequency curves, and a nonlinear regression relationship between sediment thickness and the dominant frequency was proposed using shallow drilling data. The thickness of the alluvial sediment in the basin was calculated using the proposed equation and the basic geometry of the alluvial soil was plotted along N–S and E–W oriented sections using the thickness information obtained. Finally, it was found that structural risk assessments in areas where the alluvial ground is 15 m or deeper should be prioritized by considering other soil parameters such as bedrock depth, the focusing effect, the resonance effect, the Vs30 velocity, the soil class, and the groundwater level. [ABSTRACT FROM AUTHOR]

In this study, the wind energy characteristics of Dinar region were researched. Required wind data was provided by the Dinar Meteorology Station of the Turkish State Meteorology Service. Wind data was recorded hourly between June 2015 and May 2020. The two variable Weibull probability distribution function was used to research wind characteristics of the region. Six different methods were used to calculate shape (k) and scale (c) variables of the probability distribution function. These are moment, graph, Justus empirical, energy trend, energy pattern and maximum likehood estimation methods. The performance of these methods were compared with four different statistical error analysis methods. These are root mean square error (RMSE), coefficient of determination (R2), chisquare error (X2) and mean absolute error (MAE). According to the results, maximum likehood estimation and energy trend methods have been the most successful methods in the calculation of Weibull parameters. In addition, this study is an important preliminary study in determining the wind energy characteristic of the region. [ABSTRACT FROM AUTHOR]

Trend identification procedures are used to identify systematic monotonic trendlines in a given hydro-meteorological time series recording to represent time-dependent variations as increases or decreases. Different methodologies have been proposed for such descriptions, but most of them require restrictive assumptions such as normal (Gaussian) probability distribution function (PDF), serial independence, and long sample sizes. In particular, pre-whitening and over-whitening are recommended to meet the need for serial independence, but they cannot transform a serially dependent series into a completely independent one. In this paper, a new trend methodology is proposed based on the characteristics of crossings along any given straight line within the given time series, and the sought-after trend component is the one with the maximum number of crossings. This approach does not require any restrictive assumptions. Unlike previous trend algorithms, the proposed cross-empirical trend analysis (CETA) does not give a single trend, but a series of trends at different levels within the variation range of hydro-meteorological time series records. For the sake of brevity, only three levels are considered in this article, at 10%, 50%, and 90% risk levels. The comparison of the CETA approach is presented with the classical and frequently used Mann–Kendall (MK) trend determination procedure method based on Sen's slope calculation. For very small series correlation coefficients and normal PDF function cases, CETA and the classical technique give almost the same trendline within the ± 5% error band. The application of this methodology is presented for monthly and annual discharge records of the Danube River and annual precipitation records from seven geographical regions of Turkey. [ABSTRACT FROM AUTHOR]

As the world population is getting older, care for elderly and procurement to their special needs gains importance for both national and local governments. Therefore, distribution of elderly population and their (residential) mobility behaviours gains importance to improve policies coupled in this respect. However, although demographic processes can easily be monitored and projected over time for a country, estimating distribution of certain population cohorts over space (elderly population in our case) entails difficulties. Indeed, elderly population does not show a uniform distribution in space. This study investigates spatial variation and dynamics of elderly population in Turkey, where elderly population is percolating unevenly in space. We devise two complementary ANCOVA models and a structural equations model, which suggest a disproportionate and growing share of elderly in small, inner and coastal areas, especially sun‐belt coastal districts. We conclude the study with prospective policies for elderly for central and local governments. Our findings suggest inclusive and attentive policies geared to spatial reflections of demographic processes. In particular, we favour policies focused on improved services for the elderly and spatial planning considering special populations groups, one of which is elderly population. [ABSTRACT FROM AUTHOR]

In this study, the average wind conditions and economic analyses of four identical wind turbines of three-bladed and 3 MW of rated power located in an installed wind farm abbreviated as WTPP and found in Eastern Mediterranean region of Turkey in Hatay province, were conducted. In this way, the probability density distributions based on wind directions regarding these identical wind turbines of the wind farm as well as cumulative probability density distributions regarding wind speeds for all identical wind turbines were performed. Besides, the economic analysis in terms of the present value calculation for a 3 MW rated power wind turbine was executed, in which the results demonstrated that the application of the wind turbine project of this type would be profitable. [ABSTRACT FROM AUTHOR]

Copyright of SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi is the property of Journal of Engineering Sciences & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Turkish Journal of Social Research / Turkiye Sosyal Arastirmalar Dergisi is the property of Turkish Journal of Social Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Risk management and design strategies for extreme temperatures are generally based on a 50-year return level in many national and international legislations. Recent studies have reported significant increasing trends in extreme temperature characteristics all over the world including Turkey. For such an analysis, return level mapping of climatic variables under non-stationarity conditions is a new topic. For this reason, the goal of this study was to introduce a mapping methodology for a 50-year return level of the extreme temperatures for northwest Turkey by considering the non-stationarity conditions. Generalized Extreme Value distribution was fitted for this purpose to de-trended extreme temperature time series. Multiple regression models were developed accordingly based on the physiographic parameters to interpolate point-based return levels over the study area. Observed annual maximum and minimum temperatures as well as the 50-year return levels indicated a high spatial variability over the region. According to the results of the study, Continentality Index, elevation, and latitude are determined to be the appropriate predictors for obtaining annual minimum temperature return level maps while the first two parameters are optimal for a statistical model of the maximum temperatures. Return level extreme temperature maps were produced with 2.5 × 2.5-km grids. Under climate change and its variability, it is of utmost importance for any method to consider the non-stationarity in calculations when modeling the changing conditions. The maps that are produced can be a tool for adapting to intensifying heat waves under climate change and its variability while the applied methodology can be transferred to any other region. [ABSTRACT FROM AUTHOR]

This article is motivated by the panel surveys, called Statistics on Income and Living Conditions (SILC), conducted annually on (randomly selected) country representative households to monitor EU 2020 aims on poverty reduction. We particularly consider the surveys conducted in Turkey within the scope of integration to the EU. Our main interests are on health aspects of economic and living conditions. The outcome is self-reported health that is clustered longitudinal ordinal, since repeated measures of it are nested within individuals and individuals are nested within families. Economic and living conditions have been measured through a number of individual- and family-level explanatory variables. The questions of interest are on the marginal relationships between the outcome and covariates that we address using a polytomous logistic regression with Bridge distributed random effects. This choice of distribution allows us to directly obtain marginal inferences in the presence of random effects. Widely used Normal distribution is also considered as the random effects distribution. Samples from the joint posterior densities of parameters and random effects are drawn using Markov Chain Monte Carlo. Interesting findings from the public health point of view are that differences were found between the subgroups of employment status, income level and panel year in terms of odds of reporting better health. [ABSTRACT FROM AUTHOR]

Copyright of Gumushane Universty Electronic Journal of the Faculty of Communication / Gümüshane Üniversitesi Iletisim Fakültesi Elektronik Dergisi is the property of Gumushane Universitesi Iletisim Fakultesi Elektronik Dergisi (e-GIFDER) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modelling the seismic potential of active faults and the associated epistemic uncertainty is a fundamental step of probabilistic seismic hazard assessment (PSHA). We use SHERIFS (Seismic Hazard and Earthquake Rate In Fault Systems), an open-source code allowing us to build hazard models including earthquake ruptures involving several faults, to model the seismicity rates on the North Anatolian Fault (NAF) system in the Marmara Region. Through an iterative approach, SHERIFS converts the slip rate on the faults into earthquake rates that follow a magnitude frequency distribution (MFD) defined at the fault system level, allowing us to model complex multi-fault ruptures and off-fault seismicity while exploring the underlying epistemic uncertainties. In a logic tree, we explore uncertainties concerning the locking state of the NAF in the Sea of Marmara, the maximum possible rupture in the system, the shape of the MFD and the ratio of off-fault seismicity. The branches of the logic tree are weighted according to the match between the modelled earthquake rate and the earthquake rates calculated from the local data, earthquake catalogue and palaeoseismicity. In addition, we use the result of the physics-based earthquake simulator RSQSim to inform the logic tree and increase the weight on the hypotheses that are compatible with the result of the simulator. Using both the local data and the simulator to weight the logic tree branches, we are able to reduce the uncertainties affecting the earthquake rates in the Marmara Region. The weighted logic tree of models built in this study will be used in a following article to calculate the probability of collapse of a building in Istanbul. [ABSTRACT FROM AUTHOR]

A methodology using the standardised precipitation index is proposed to develop critical drought intensity-duration-frequency (IDF) curves. We define dry periods within which we recognise droughts of different durations. The most severe drought for each drought duration in each year is called the critical drought. The total probability theorem-coupled frequency analysis is used to determine the best-fit probability distribution function of drought severity, which is then converted to intensity. The generalised extreme value probability distribution function is found to best fit the critical drought severity. The methodology is implemented using monthly precipitation data for a meteorological station in Turkey. The critical drought intensity decreases linearly with increasing drought duration, whereas the return period increases exponentially when the drought becomes more severe. The site-specific IDF curves furnished with an empirical relationship between the intensity and return period allow one to characterise the drought not by an index-based intensity but by its return period. This kind of presentation is physically easier to understand, in particular for stakeholders and decision makers in practice. [ABSTRACT FROM AUTHOR]

This study aims to examine and statistically analyze the cases of food poisoning in Turkey between 2016 and 2020, and the number of people affected by these cases. The data on food poisoning were obtained from news sources published in the written and visual media while weather temperature and relative humidity values were obtained from the Ministry of Agriculture and Forestry. Frequency distributions and Kruskal Wallis and Bonferroni non-parametric tests were used to evaluate the data. A total of 504 cases of food poisoning (100.8 cases/year, 42 cases/month) were experienced in Turkey between 2016 and 2020, and the estimated number of people affected by those cases is 27,196. Surprisingly, most cases of food poisoning occurred in autumn and winter while the lowest number of cases took place in summer. Students and employees were most affected by food poisoning. No direct correlation of food poisoning with ambient temperature and relative humidity was determined. The study is the first research conducted in Turkey in this area, and can be used to develop strategies and policies for food safety. [ABSTRACT FROM AUTHOR]

This study was prepared using exploratory sequential mixed methods research design. The aim of this study is to reveal the current situation of articles in the field of guitar in Turkey. The population of this research is all articles that were published of guitar field. The sample of the study is composed of guitar articles in Dergi Park and SOBİAD database. In this context, guitar articles in these databases were scanned and 85 articles that made up the sample were accessed. These articles were analyzed according to 9 criteria; number of authors, year of publication, journal in which they are published, research subject, research method, research type, data collection tools, field of publication and language of publication. While determining the criteria, the literature review was used and the opinions of 3 field experts were taken. Research data were collected by document review. The articles that make up the sample were examined according to the specified criteria and the examined criteria were tabulated. The results of the study were obtained by interpreting the tables containing the frequency distribution and percentages of the relevant criteria. In addition, some suggestions were made to contribute to the field. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Aksaray University Faculty of Economics & Administrative Sciences / Aksaray Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Aksaray University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim: As in the whole world, the frequency and distribution of cancers in our country show regional differences, and sufficient data are not available in terms of etiological factors. In this study, Dicle University Faculty of Medicine Department of Pathology of Dicle University with the data we have obtained from the records of the incidence of cancer in the region, our region belongs in the previous year's work and Turkey is intended to research cancer distributions by gender by comparing it with data. Material and Method: The records of 64.256 patients consisting of needle biopsy, endoscopic biopsy, punch biopsy, excision and resection materials that came to Dicle University Faculty of Medicine Pathology Department between January 2012 and January 2017 were analyzed retrospectively. Results: Of the patients we examined, 7644 (11.9%) had malignant tumors. Of the patients with malignant tumors, 3.792 (49.6%) were male and 3.852 (50.4%) were female. The first five most common cancers were breast (17.6%), lung (14.4%), skin (10%), thyroid (8.4%), colorectal (6.3%), respectively. The first five of the most common cancers in male patients are lung (23.84%), prostate (11.84%), skin (11.15%), bladder (8.31%), lymphoma (7.62%), breast in women (34.11%), thyroid (13.81%), skin (8.80%), colorectal (5.78%) and lung (5.14%) cancers. Conclusion: In this study where we investigated the frequency of cancer in Diyarbakir and its region, the most common breast cancer and skin cancer, which is in third place in both sexes, come to the fore. Thyroid cancers also draw attention in the fourth row. Our data can help cancer epidemiology of Diyarbakir and its region and contribute to taking precautions for cancer patients in the region. [ABSTRACT FROM AUTHOR]

We describe the process of pairing M4+ earthquakes reported in the routine catalogues of two seismic networks in Turkey and present the resulting products: (i) hypocentre locations and magnitudes and (ii) minimum 1-D velocity model with station delays for the combined station network. The two networks are the Kandilli Observatory (KOERI) and the National Earthquake Department (AFAD) and the data cover the decade 2007–2016. The seismic stations of these two networks spatially overlap within Turkey, and with their average station spacing of about 60 km, they potentially detect all events of magnitude ≥4 independently. We first obtain separate AFAD and KOERI catalogues using a series of joint hypocentre inversions that allow us to detect outliers and problematic events. We establish separate minimum 1-D velocity models and station delays for each catalogue and reduce the average inversion residuals by 75 per cent compared to our first joint hypocentre inversion using the original catalogue event locations. We then pair M4+ events from AFAD (1219) and KOERI (1271) catalogues using a spatiotemporal window and test if the combined observations indeed belong to the same event. In these tests, we compare the hypocentre location residuals of the combined observations to those of the two individual events, apply epicentral distance limits between the individual and the paired events and assess qualitatively a simple probabilistic solution of the events. As a result, we get 1145 paired events. We finally obtain a minimum 1-D velocity model with delays for all seismic stations of AFAD and KOERI combined and relocate the entire set of events. These include all paired events plus M4+ earthquakes reported by AFAD or KOERI that could not be paired (500). The velocity model has a well-defined Moho at a depth of 32 km. The station delays for both networks regionally correspond very well and exhibit some correlation with the regional subsurface temperature field. The well-locatable hypocentres of the new M4+ catalogue have an epicentre uncertainty of 3 km and a depth uncertainty of 4 km. We ascribe to each paired earthquake a magnitude equal to the average of the reported magnitudes by AFAD and KOERI. The new magnitude frequency distribution is similar to those of AFAD and KOERI for M4+ events. Except for events of magnitude larger than 5.5, there is no systematic bias in the magnitudes reported by AFAD and by KOERI, and the standard deviation is 0.3. [ABSTRACT FROM AUTHOR]

The climate change impact appears as a decreasing or increasing monotonic trend in hydro-meteorology time series records due to greenhouse gas (GHG) emissions causing to global warming and climate change impacts. On the other hand, there may be abrupt changes in the form of jumps in these series due to natural and engineering activities. Although trend identification methods are rather common in the literature, jump determination conventional methodologies are rather rare and their applications present some restrictive asumptions like the serial independence and normal (Gaussian) probability distribution function (PDF). The methodology presented in this paper is away from each of such assumptions and it depicts the minimum number of upcrossing along horizontal truncation levels within the time series variation domain. The applications of the methodology are given for annual Danube River discharge records, Romania; New Jersey rainfall and temperature records, USA; monthly rainfall records and Van Lake level fluctuations, Turkey. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to describe precisely the wind speed regime and characteristics of a runway of an International Airport, the north-western part of Turkey. Design methodology approach: Three different probability distributions, namely, Inverse Gaussian (IG), widely used two-parameter Weibull and Rayleigh distributions in the literature, are used to represent wind regime and characteristics of the runway. The parameters of each distribution are estimated by the pattern search (PS)-based heuristic algorithm. The results are compared with the other three methods-based numerical computation, including maximum-likelihood method, moment method (MoM) and power density method, respectively. To evaluate the fitting performance of the proposed method, several statistical goodness tests including the mostly used root mean square error (RMSE) and chi-squared (X2) are conducted. Findings: In the light of the statistical goodness tests, the results of the IG-based PS attain better performance than the classical Weibull and Rayleigh functions. Both the RMSE and X2 values achieved by the IG-based PS method lower than that of Weibull and Rayleigh distributions. It exhibits a better fitting performance with 0.0074 for RMSE and 0.58 × 10−4 for X2 for probability density function (PDF) in 2012 and with RMSE of 0.0084 and X2 of 0.74 × 10−4 for PDF in 2013. As regard the cumulative density function of the measured wind data, the best results are found to be Weibull-based PS with RMSE of 0.0175 and X2 of 3.25 × 10−4 in 2012. However, Weibull-based MoM shows more excellent ability in 2013, with RMSE of 0.0166 and X2 of 2.94 × 10−4. Consequently, it is considered that the results of this study confirm that IG-based PS with the lowest error value can a good choice to model more accurately and characterize the wind speed profile of the airport. Practical implications: This paper presents a realistic point of view regarding the wind regime and characteristics of an airport. This study may cast the light on researchers, policymakers, policy analysts and airport designers intending to investigate the wind profile of a runway at the airport in the world and also provide a significant pathway on how to determine the wind distribution of the runway. Originality value: Instead of the well-known Weibull distribution for the representing of wind distribution in the literature, in this paper, IG distribution is used. Furthermore, the suitability of IG to represent the wind distribution is validated when compared with two-parameter Weibull and Rayleigh distributions. Besides, the performance and efficiency of PS have been evaluated by comparing it with other methods. [ABSTRACT FROM AUTHOR]

The temporal variability in yearly and seasonal extreme precipitation across Turkey is investigated using stationary and nonstationary frequency approach. Four frequency distributions namely, generalized extreme value (GEV), gumbel, normal, and lognormal distributions are used for the historical period (1971–2016) as well as the projection period (2051–2100). The nonstationarity impacts are determined by calculating the percentage difference of return levels (30 years) between stationary and nonstationary cases for both periods. The results are presented as nonstationarity impact maps across Turkey, providing information about the spatial variability of the magnitude of impacts as well as the impact types, i.e., the increase or decrease in return levels of extreme precipitation. For nonstationarity analysis during the projection period, the projected precipitation data is obtained from a 12-member ensemble of the Coordinated Regional Downscaling Experiment (CORDEX) regional climate models (RCM) based on the worst emission scenario (RCP8.5). In addition to this, the effects of bias-corrections on stationarities are also investigated for selected RCMs. Performance evaluation of CORDEX ensemble members suggested significant intramodel and intraregion variability in the simulation of historical precipitation. Overall, GEV provided the best fit while normal distribution provided the worst fit to precipitation extremes. However, with a few exceptions, all the distributions exhibited a similar pattern for the historical impacts of nonstationarities across the country. The yearly nonstationarity impacts for the 30-year return level reached 35, 30, 25, and 20% for the Mediterranean, Aegean, Marmara, and Black sea regions, respectively, while a mixed type of nonstationarity impacts was found in Central, Eastern, and South-Eastern Anatolia regions. Moreover, the magnitude and impact type of nonstationarity showed important variations between the seasons. The ensemble analyses of CORDEX-based projected precipitation demonstrated that during the projection period, the nonstationarity impacts are found to be different in magnitude and type as compared to the impacts during the historical period in many regions (particularly in the eastern part of Turkey). The 30-year return levels of extreme precipitations are expected to increase (up to 30%) across Turkey in the yearly, winter, spring, and autumn seasons during the projection period. However, during the same period, the summer extremes in Eastern Anatolia and Mediterranean regions decreased (up to 30%) with nonstationarity. Projected increases in the precipitation extremes lead to more floods and winter storms, while decreases in the summer precipitations will further dwindle water availability. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to use multivariate statistical methods with asymmetric distributions approach, chemical analysis, and inductively coupled plasma–mass spectrometry (ICP-MS) device. We investigate data of heavy metal content from Akcay Riverwater to the Mediterranean involving Finike sea coast at Turkey. We determine the chemical content, origin of heavy metals of the surface water in Akcay River, which flows into the Mediterranean realted to the above-mentioned region by multivariate statistical analysis, pollution indices, and density maps involving numerical comments by numbers. With the help of special numbers represented by special chemical components and simmetric statistical methods given above, in this paper, we obtain many new relations and results. Furhermore, we give some comments, observations, and remarks about the results of this paper. These results have a high potential to be used not only in engineering fields and health sciences, but also in applied mathematics, statistics, and other fields. [ABSTRACT FROM AUTHOR]

Extreme maximum (Tx) and extreme minimum temperature (Tn) frequency distributions during summer and winter for blocked conditions were analyzed within Turkey during the period from 1977 to 2016 by using observational data. The Tx (0.5–0.8%) and Tn (0.4–2.0%) frequencies vary between these values for the entire period during summer. However, Tx varies between 0.0 and 1.0, while Tn varies between 0.8 and 2.4 during winter. It is quite clear that atmospheric blocking has a greater cooling effect during winter. The maximum values for Tx and Tn are observed when the block center located within the easternmost sector impacting Turkey for summer. The maximum Tx frequency is observed in association with blocking in the westernmost sector, and the maximum Tn frequency is observed with blocking in the easternmost sector impacting Turkey during the winter season. Block intensity has almost no impact on Tx frequency although it has enhancing effect on Tn frequency during the summer. For winter, block intensity has a decreasing effect on both the maximum Tn and maximum Tx. The maximum Tx and Tn values increase with the block size for the summer. During the winter, the maximum Tx frequency decreases with the increase in the size of a blocking event; however, the greatest Tn frequency is observed within the 0°–30° E sector and lowest within the 30° E–60° E sector. The block duration has an enhancing influence on the maximum Tx value, while maximum Tn is observed during short-duration events and a minimum is observed during moderate-duration events during the summer season. For the winter season, the block duration has a decreasing effect for Tx frequencies and increasing effect for Tn. [ABSTRACT FROM AUTHOR]

Copyright of Gumushane Universty Electronic Journal of the Faculty of Communication / Gümüshane Üniversitesi Iletisim Fakültesi Elektronik Dergisi is the property of Gumushane Universitesi Iletisim Fakultesi Elektronik Dergisi (e-GIFDER) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)